There are 1 repository under depthai topic.
Running Google Mediapipe Hand Tracking models on Luxonis DepthAI hardware (OAK-D-lite, OAK-D, OAK-1,...)
Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite, ONNX, OpenVINO, Myriad Inference Engine blob and .pb from .tflite. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support. Supports inverse quantization of INT8 quantization model.
Python scripts for performing 6D pose estimation and shape reconstruction using the CenterSnap model in ONNX
Android example to get the rgb and disparity images from the OAK-D device connected to a phone.
ROS2 driver for OAK cameras
A POC project for OpenCV Spatial AI Competition
Unity project with an example on how to run the depthai library in Android.
Python scripts performing on devive semantic segmentation using the TopFormer model in depthai.
Face Recognize System on camera AI OAK1
Sample projects to use DepthAI + OpenCV with OAK-D cameras in C++
MiniPupper robot teleoperation via ROS and WebRTC
A Computer Vision and SLAM platform based oak-d and livox.
Single Shot MultiBox Detector deployed on a OAK-D Lite cam via DepthAI
This library is a set of tools to help create DepthAI pipelines and run depthai devices in a standard way.
DepthAI tutorials in Jupyter Notebooks...more coming soon.
DepthAI camera's video and still image outputs to a RTSP H264 video stream and JPEG HTTP server.
Record RGB and stereo video with timestamp using DepthAI OAK-D
A computer vision and machine learning pipeline on a distributed framework. Designed for an embedded network on low voltage IoT hardware.
Repository is part of my BSc thesis with title "Gesture recognition in video streams on an embedded device"
A minimal demo to run depthai time of flight cameras with an RGB overlay
Embedded AI solution to aid people with visual impairement involved in research by converting equations and texts from scientific books into Nemeth-Braille
OAK module that groups all the scripts and functions necessary for neonatal infant monitoring.
Collision Avoidance System based on yolov5 and OAK-D stereo camera
Human Exercise Detection. Depth AI pipeline on device (Luxonis OAK-D light) and host (Raspberry PI 4) for the Tension Terminator. Camera device is installed overhead. Detection is for exercise informations (type, time, correct movement).
Detecting time periods when cat eats at home using ML
Get aligned depth from RGB and stereo video which record with DepthAI OAK-D
Record RGB and aligned depth with DepthAI OAK-D